Proceedings of the Korean Institute of Intelligent Systems Conference (한국지능시스템학회:학술대회논문집)

Korean Institute of Intelligent Systems (한국지능시스템학회)
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APPROXIMATIVE INFERENCE IN HIERARCHICAL STRUCTURED RULE BASES

  • Koczy, Laszlo T. (Dept. of Telecommunication and Telematics Technical University of Budapest) ;
  • Hirota, Kaoru (Dept. of Instrumentation and Control Engineering Hosei University College of Engineering)
  • Published : 1993.06.01
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Abstract

The paper discusses the problem of controlling systems with a very high number of input variables effectively by fuzzy If . . . then rules. The basic idea is the partition of the state space into domains, which step can be done even iteratively several times, and every domain has its own sub rule base referring to a considerably lower number of variables than the original space. In this manner the number of necessary rules is drastically reduced and time complexity of the control algorithm remains acceptable.

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